Predisposition to Myelodysplastic Syndrome with Deletion 5q Is Associated with TP53 Codon 72 Genotype
Notice bibliographique
Résumé
Abstract Abstract 612 Background: Chromosome 5q deletion (del5q) is the most common cytogenetic abnormality in myelodysplastic syndrome (MDS). Although haplodeficiency of several genes may contribute to the disease phenotype, allelic deletion of the ribosomal protein S14 (RPS14) gene is a key effector of the hypoplastic anemia. Disruption of ribosome assembly arising from RPS14 deletion leads to nucleolar stress that triggers p53 activation. In a murine model of the human 5q- syndrome, TP53 inactivation was alone sufficient to rescue the hematologic phenotype, indicating that the molecular pathogenesis of del(5q) MDS is p53-dependent. The tumor suppressor TP53 gene is a key regulator of stem cell homeostasis and senescence. A well described single nucleotide polymorphism (SNP) located at codon 72 in the proline-rich, pro-apoptotic domain of TP53 has been linked to cancer and mutagen susceptibility, and treatment outcome. Substitution of a cytosine (‘C’ allele) for the more common guanine (‘G’ allele) results in translation of a proline rather than arginine residue at position 72, with diminished apoptotic potential. Given the pathogenetic role of p53 in del(5q) MDS, we hypothesized that homozygosity for the ‘C’ allele may be associated with disease predisposition. Methods: Bone marrow and blood samples were investigated from 118 del(5q) MDS patients, 102 non-del(5q) MDS patients, and 98 healthy controls. Genomic DNA was extracted and codon 72 of the TP53 gene was amplified by PCR. Forward and reverse Sanger sequencing was performed to determine genotype. Relationship to disease specific features at diagnosis including cytogenetic risk category, IPSS score, blast percentage, and age were investigated as well as the relationship to response to lenalidomide and AML transformation using SAS software (Version 9.2, SAS Institute Inc., Cary, NC, USA). Results: Genotype distribution significantly differed between del(5q) MDS patients (18% CC, 47% CG, and 35% GG), non-del(5q) MDS patients (9% CC, 58% CG, and 33% GG),and healthy controls (7% CC, 43% CG, and 50% GG) (p=0.01). The frequency of the homozygous CC genotype was >2x greater in del(5q) MDS (18%) compared to both non-del(5q) MDS (9%) and healthy controls (7%) (p=0.05). There was no significant frequency difference between non-del(5q) and healthy controls. Del(5q) MDS patients were >6 times more likely to carry the CC genotype vs. GG when compared to healthy controls [odds ratio (OR)=6.71, 95% CI: 1.56 to 28.86], whereas non-del(5q) patients were >3 times more likely to carry the CC genotype vs. GG when compared to healthy controls (OR=3.87, 95% CI: 0.66 to 22.71). The corresponding ‘C’ allele frequency was significantly greater among del(5q) MDS patients (41.7%) compared to healthy controls (28.6%) (p=0.006), and approached significance in non-del(5q) patients (37.8%) versus controls (p=0.06). There was no association between TP53 R72P genotype and cytogenetic risk group in either del(5q) (p=0.67) or non-del(5q) MDS patients (p= 0.60), IPSS (del5q, p=0.29; non-del5q, p=0.89), or response to lenalidomide (del5q, p=0.57; non-del5q p=0.89). Mean age at diagnosis was significantly (p=0.04) lower in del(5q) MDS (67.4 years; SD=11.1 years) compared to non-del(5q) MDS patients (70.8 years; SD=9.1years), although significant differences in age according to TP53 R72P genotype were not apparent in either MDS cytogenetic group (del5q, p=0.99; non-del5q, p=0.89). Conclusion: Our findings indicate that the TP53 R72P homozygous CC genotype occurs with significantly greater frequency in del(5q) MDS compared to both non-del(5q) MDS patients and healthy controls, suggesting that this polymorphism may play a key role in the pathogenesis of and predisposition to del(5q) MDS. Disclosures: Kurtin: Celgene: Honoraria. Maciejewski:Celgene: Research Funding; Eisai: Research Funding; Alexion: Consultancy. Nevill:Celgene: Honoraria. Karsan:Celgene: Research Funding. List:Celgene: Research Funding.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».